دورية أكاديمية
Correlation-based Graph Smoothness Measures In Graph Signal Processing
| العنوان: | Correlation-based Graph Smoothness Measures In Graph Signal Processing |
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| المؤلفون: | Miettinen, Jari, Vorobyov, Sergiy A., Ollila, Esa, Wang, Xinjue |
| المساهمون: | Sergiy Vorobyov Group, Department of Information and Communications Engineering, Aalto-yliopisto, Aalto University |
| سنة النشر: | 2023 |
| المجموعة: | Aalto University Publication Archive (Aaltodoc) / Aalto-yliopiston julkaisuarkistoa |
| مصطلحات موضوعية: | graph autocorrelation, graph autocovariance, Graph signal processing, graph smoothness measures |
| الوصف: | Publisher Copyright: © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved. ; Graph smoothness is an important prior used for designing sampling strategies for graph signals as well as for regularizing the problem of graph learning. Additionally, smoothness is an appropriate assumption for graph signal processing (GSP) tasks such as filtering or signal recovery from samples. The most popular measure of smoothness is the quadratic form of the Laplacian, which naturally follows from the factor analysis approach. This paper presents a novel smoothness measure based on the graph correlation. The proposed measure enhances the applicability of graph smoothness measures across a variety of GSP tasks, by facilitating interoperability and generalizing across shift operators. ; Peer reviewed |
| نوع الوثيقة: | text |
| وصف الملف: | 1848-1852; application/pdf |
| اللغة: | English |
| ردمك: | 978-94-6459-360-0 94-6459-360-1 |
| تدمد: | 2219-5491 20240104 |
| العلاقة: | European Signal Processing Conference; 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings; Miettinen , J , Vorobyov , S A , Ollila , E & Wang , X 2023 , Correlation-based Graph Smoothness Measures In Graph Signal Processing . in 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings . European Signal Processing Conference , European Signal Processing Conference (EUSIPCO) , pp. 1848-1852 , European Signal Processing Conference , Helsinki , Finland , 04/09/2023 . https://doi.org/10.23919/EUSIPCO58844.2023.10289784Test; PURE UUID: 28ac12dc-26bc-493a-9e57-cf91ecfbdb24; PURE ITEMURL: https://research.aalto.fi/en/publications/28ac12dc-26bc-493a-9e57-cf91ecfbdb24Test; PURE LINK: http://www.scopus.com/inward/record.url?scp=85178363701&partnerID=8YFLogxKTest; PURE FILEURL: https://research.aalto.fi/files/130876054/0001848.pdfTest; https://aaltodoc.aalto.fi/handle/123456789/125374Test; URN:NBN:fi:aalto-202401041063 |
| DOI: | 10.23919/EUSIPCO58844.2023.10289784 |
| الإتاحة: | https://doi.org/10.23919/EUSIPCO58844.2023.10289784Test https://aaltodoc.aalto.fi/handle/123456789/125374Test |
| حقوق: | openAccess |
| رقم الانضمام: | edsbas.7DDB1F5B |
| قاعدة البيانات: | BASE |
| ردمك: | 9789464593600 9464593601 |
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| تدمد: | 22195491 20240104 |
| DOI: | 10.23919/EUSIPCO58844.2023.10289784 |